Course Info

Course Description:

The goal of this course is to provide Professional Masters students with industry mentorship and real-world data science training. Beyond-classroom educational opportunities are an excellent way to gain practical experience on a substantial project, to learn advanced skills, to collaborate with a professional PhD researcher, to form a connection to a data science company, and to work in a team with other graduate students. Industry partners propose semester-long data science projects. Students form three-to-five-person teams, each of which work on one project throughout the semester, under the guidance of their industry mentor, additional PhD student mentors, and the course faculty instructor. Furthermore, in weekly class meetings all students receive professional development education, data science hardware and software infrastructure training, data science research presentations, and career advice. Student teams gain valuable oral presentation experience and feedback by regularly presenting their work-in-progress, as well as a final public presentation of their project at the end of the semester. Advantages of these industry relationships often include access to rich industry-scale data, learning about real-world problems, and making industry connections useful for the future.

Assignments & Grading

You will be evaluated by the instructors on your work in the course as described below. There will also be one or two intra-team peer feedback opportunities, which will be incorporated into your grade as described below:

  • Project Presentations
    • Proposal Presentation (10%)
    • Midpoint Presentation (15%)
    • Final Presentation (15%)
  • Project Reports
    • Proposal Report (10%)
    • Midpoint Report (15%)
    • Final Report (15%)
  • Poster (10%)
  • Peer Evaluation (5%)
  • Class Participation (5%)

Minor revisions may be made to grading rubric in the first two weeks of the course and will be announced to the students on the mailing list.

Lecture Format

The course meetings will take a variety of forms including: research method strategies and best practices; teams giving presentations on their current progress; panels and discussion about career paths; and more. Please see the schedule for more information.